Mid-Air Collision Risk for Urban Air Mobility: A Review

Urban Air Mobility (UAM) introduces new safety challenges as small unmanned aircrafts begin to operate at high density in complex urban environments. Traditional air traffic management (ATM) systems developed for manned aviation are unable to accommodate the autonomy, mission diversity, and dynamic obstacle conditions typical of low-altitude operations. This review examines recent research on mid-air collision risk and airspace safety modeling for UAM and identifies key challenges in adapting existing safety concepts to small-scale and autonomous flight. The study compares international management frameworks of the United States, Europe, and China. Then analyzes representative airspace structures such as Free, Layered, Zoned, and Pipeline configurations. It further reviews deterministic and probabilistic separation models, geometric and optimization-based avoidance strategies, and structured airspace approaches such as the virtual-tube concept for coordinated swarm navigation. The findings highlight the lack of integrated models that couple human, energy, and communication factors into quantitative risk assessment. The paper concludes by outlining future research needs in uncertainty modeling, digital-twin simulation, and interoperability to support safe and scalable UAM development.

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Publication Details

Journal
Drones
Published
2026-03-17
DOI
https://doi.org/10.3390/drones10030211
Primary Topic
Air Traffic Management and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Mid-Air Collision Risk for Urban Air Mobility: A Review

Rao Fu, Yan Gao, Kaiquan Cai, Jun Li et al.
Drones
Air Traffic Management and Optimization
article

Mid-Air Collision Risk for Urban Air Mobility: A Review

Rao Fu, Yan Gao, Kaiquan Cai, Jun Li, Quan Quan, Yang Liu, Rongkun Jiang
article en

Abstract

Urban Air Mobility (UAM) introduces new safety challenges as small unmanned aircrafts begin to operate at high density in complex urban environments. Traditional air traffic management (ATM) systems developed for manned aviation are unable to accommodate the autonomy, mission diversity, and dynamic obstacle conditions typical of low-altitude operations. This review examines recent research on mid-air collision risk and airspace safety modeling for UAM and identifies key challenges in adapting existing safety concepts to small-scale and autonomous flight. The study compares international management frameworks of the United States, Europe, and China. Then analyzes representative airspace structures such as Free, Layered, Zoned, and Pipeline configurations. It further reviews deterministic and probabilistic separation models, geometric and optimization-based avoidance strategies, and structured airspace approaches such as the virtual-tube concept for coordinated swarm navigation. The findings highlight the lack of integrated models that couple human, energy, and communication factors into quantitative risk assessment. The paper concludes by outlining future research needs in uncertainty modeling, digital-twin simulation, and interoperability to support safe and scalable UAM development.

DronesVol. 10(3)
Tiangong University (CN), Beijing Jiaotong University (CN), Beijing Satellite Navigation Center (CN), Beihang University (CN)
Sustainable cities and communities
Openalex Percentile: Top 17%
Air Traffic Management and Optimization
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Mid-Air Collision Risk for Urban Air Mobility: A Review — Rao Fu, Yan Gao, et al. · Drones (2026) | TGRS Research Map | TGRS